Human Characteristics

Human Characteristics

T-Test Analysis in the data set
As we know that the Human characteristics are base upon several features like eye color, facial features, height, hair colors, and many more. For doing the frequency distribution among the data which we have been retained based upon the different characteristics based on the t-test is described below:

As we know that the t-test determines if they have the assistance of null-hypothesis. T-test determines how much the data from both fields are different from each other. For this purpose, initially, we take the average values of both male and female data. After that, the unknown scale data is replaced by the estimate based data. The t-test determines that the moth men and women are equal in the normal distribution. For this purpose, the variance value among Men and Women is also the same. The below graph can easily determine the graph among the men and women and the distribution value:

When we have to determine the t-test result, the value of standard deviation and the size of the data is known, but their mean values are always equal to zero. And from the above graph, we can see clearly that the mean values of the men and women are zero too. To determine the frequency distribution, we use hypothetical statistics. As here, we are using the data set of 79 people. So that degree of freedom, in this case, is n-1, which is 78 because our data set is independent.  To determine the distribution of T-statistics following formula is using described below:

T = Z / √V/ν= Z √ν/V

The details of the following parameters given below:

·         Z = Z describes the normally distributed values where the expected value of the variance is 0 or 1, respectively.

·         V = V is a parameter that has a chi-squared distribution with ν degrees of freedom

·         Both the values of Z and V are highly independent parameters.

The value of both mean and standard deviation in both cases, men and women are also equal here. The importance of Mean in women’s case is also one, and in men, the situation is also 1.

Bar Charts
The data set of the hairs color along with their distribution of the frequency values given below:

S.no
Hair Color
Frequency
1-
Brown
48
2-
Blond
16
3-
Black
12
4-
Ginger
3
The bar graph of the following data set described below:

From the above graph, we can see clearly that the frequency of the brown color people in the data is more compare to the other color. Similarly, the least frequency distribution value of the hair color in the data set is grey.

Similarly, the data set of eye color given below:

S.no
Eye color name
Frequency
1-
Brown
45
2-
Green
9
3-
Grey
2
4-
Blue
19
5-
Green/Blue
4
The bar graph of the following dataset described below:

Data Set and the Literature review based evidence
As we can see that the data set based upon the following feature mentioned below:

1-      Freckles

2-      Eye color

3-      Hair color

4-      Free ear lobe

5-      Window  peak

6-      Dimples

7-      Tongue Rolling

8-      Right and Left-handed

9-      Color Blindness

10-  Likes and Dislike

All of these characteristics used to determine either the human components in both men and women. Most of the time, the data collected by different surveys. In the collection of the data set, they have primarily used the following three techniques mentioned in detail below:

Population-based sampling:
In the next data set, they have only included the samples based upon the population-based study concerning the specific pigmentation traits.

Sample size:
To continue the project in the sporadic reports, the standard deviation values must be stable and equal in both sample populations. In the following data set, the minimum number of eye color is two, and the hair color is three, respectively. 95% confidence intervals assessed the uncertainty of the derived prevalence estimates. Studies whose total sample size failed the thresholds stated above excluded.

Plausibility:
Considers had to be reliable in their introduction to be considered dependable. We experienced many thinks about where pigmentation category extents did not match the whole up to solidarity.